Dexcom (DXCM) Operating Expenses (2010 - 2026)
Dexcom's Operating Expenses was $511.7 million in Q2 2026, up 7.5% from $476.2 million a year earlier and up 3.4% from the prior quarter.
Dexcom (DXCM) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Dexcom's Operating Expenses was $1.97 billion through Jun 30, 2026, up 6.8% year-over-year; for FY2025, it came in at $1.89 billion, up 2.8% from FY2024.
- Operating Expenses has now increased for six consecutive years, with a five-year compound annual growth rate of 14.0% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $1.84 billion in FY2024 (+8.7%), $1.69 billion in FY2023 (+13.4%), $1.49 billion in FY2022 (+5.5%) and $1.41 billion in FY2021 (+44.3%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses in data going back to Q2 2010.
- Compared with a year earlier, Operating Expenses has increased for five straight quarters, with growth averaging 5.0% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2021 (growth of 59.9%); the worst was Q4 2022 (a decline of 11.9%).
- Per Business Quant data, DXCM's Operating Expenses in the three quarters before Q2 2026 was $495 million (Q1 2026), $469.7 million (Q4 2025) and $488.9 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 251.30 Bn | 230.45 Bn | 4.88 Bn | 9.91 Bn |
| 2 | Abbott Laboratories | 174.70 Bn | 145.78 Bn | 7.27 Bn | 10.90 Bn |
| 3 | Danaher | 158.94 Bn | 142.76 Bn | 3.61 Bn | 2.48 Bn |
| 4 | Intuitive Surgical | 145.87 Bn | 125.42 Bn | 1.96 Bn | 988.50 Mn |
| 5 | Medtronic | 111.49 Bn | 77.36 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 106.96 Bn | 93.08 Bn | 4.50 Bn | 2.84 Bn |
| 7 | Boston Scientific | 63.62 Bn | 58.63 Bn | 3.85 Bn | 2.67 Bn |
| 8 | Edwards Lifesciences | 50.80 Bn | 34.92 Bn | 1.35 Bn | 840.10 Mn |
| 9 | Becton Dickinson | 49.59 Bn | 46.74 Bn | 2.32 Bn | 4.32 Bn |
| 10 | Dexcom | 32.70 Bn | 23.01 Bn | 830.00 Mn | 511.70 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 511.70 Mn |
| Mar 31, 2026 | 495.00 Mn |
| Dec 31, 2025 | 469.70 Mn |
| Sep 30, 2025 | 488.90 Mn |
| Jun 30, 2025 | 476.20 Mn |
| Mar 31, 2025 | 455.30 Mn |
| Dec 31, 2024 | 466.90 Mn |
| Sep 30, 2024 | 441.80 Mn |
| Jun 30, 2024 | 468.70 Mn |
| Mar 31, 2024 | 460.80 Mn |
| Dec 31, 2023 | 439.70 Mn |
| Sep 30, 2023 | 417.80 Mn |
| Jun 30, 2023 | 418.30 Mn |
| Mar 31, 2023 | 415.40 Mn |
| Dec 31, 2022 | 415.90 Mn |
| Sep 30, 2022 | 346.70 Mn |
| Jun 30, 2022 | 372.50 Mn |
| Mar 31, 2022 | 356.80 Mn |
| Dec 31, 2021 | 472.00 Mn |
| Sep 30, 2021 | 328.60 Mn |
Dexcom Operating Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=operating-expenses&ticker=DXCM&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "DXCM", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=DXCM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();